Dr. Somdip Dey
Nosh Technologies
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Academic Career Length
15Years (2012-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
Somdip DeySSSuman Saha
Suman Saha
Amit Kumar Singh
Klaus McDonald-MaierFood safety is an important issue in today’s world. The traditional agri-food production system does not offer easy traceability of the produce at any point of the supply chain, and hence, during a food-borne outbreak, it is very difficult to sift through food production data to track produce and the origin of the outbreak. In recent years, the blockchain based food production system has resolved this challenge; however, none of the proposed methodologies makes the food production data easily accessible, traceable and verifiable by consumers or producers using mobile/edge devices. In this paper, we propose FoodSQRBlock (Food Safety Quick Response Block), a blockchain technology based framework that digitises the food production information and makes it easily accessible, traceable and verifiable by the consumers and producers by using QR codes. We also propose a large-scale integration of FoodSQRBlock in the cloud to show the feasibility and scalability of the framework, as well as give an experimental evaluation to prove this.
1 September 2018
Conference Paper
Somdip DeyRecently we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority-attack from taking place.
Journal Article
Somdip DeySSSuman Saha
Suman SahaAmit Kumar SinghKlaus McDonald-MaierFood waste is an important social and environmental issue that the current society faces, where one third of the total food produced is wasted or lost every year while more than 820 million people around the world do not have access to adequate food. However, as we move towards a decentralized Web 3.0 enabled smart city, we can utilize cutting edge technologies such as blockchain, artificial intelligence, cloud computing and many more to reduce food waste in different phases of the supply chain. In this paper, we propose SmartNoshWaste—a blockchain based multi-layered framework utilizing cloud computing, QR code and reinforcement learning to reduce food waste. We also evaluate SmartNoshWaste on real world food data collected from the nosh app to show the efficacy of the proposed framework and we are able to reduce food waste by 9.46% in comparison to the originally collected food data based on the experimental evaluation.
23 March 2020 in IEEE Design & Test
Journal Article
Amit Kumar SinghSomdip DeyKlaus McDonald-MaierKBKarunakar Reddy Basireddy
Karunakar Reddy Basireddy
Geoff MerrettBABashir M. Al-Hashimi
Bashir M. Al-Hashimi
Multi-core mobile platforms are on rise as they enable efficient parallel processing to meet ever-increasing performance requirements. However, since these platforms need to cater for increasingly dynamic workloads, efficient dynamic resource management is desired mainly to enhance the energy and thermal efficiency for better user experience with increased operational time and lifetime of mobile devices. This article provides a survey of dynamic energy and thermal management approaches for multi-core mobile platforms. These approaches do either proactive or reactive management. The upcoming trends and open challenges are also discussed.
25 June 2012 in International Journal of Modern Education and Computer Science
Journal Article
24 October 2019 in IEEE Access
Journal Article
Somdip DeyASAmit Kumar Singh
Amit Kumar Singh
Dilip K. PrasadKlaus McDonald-MaierAutomated feature extraction from program source-code such that proper computing resources could be allocated to the program is very difficult given the current state of technology. Therefore, conventional methods call for skilled human intervention in order to achieve the task of feature extraction from programs. This research is the first to propose a novel human-inspired approach to automatically convert program source-codes to visual images. The images could be then utilized for automated classification by visual convolutional neural network (CNN) based algorithm. Experimental results show high prediction accuracy in classifying the types of program in a completely automated manner using this approach.
About Me
Dr. Somdip Dey is an Embedded Artificial Intelligence scientist, engineer, entrepreneur, AI art and music producer, and TED speaker. He currently holds the position of CEO of Nosh Technologies, a Lecturer of Data Science at York St John University, and a Lecturer of Computer Science at the University of Essex. He is also the Danah Zohar Professor of Quantum Philosophy and a Professor of Practice (AI/ML) at Woxsen University, India. He has more than 14 years of industrial experience including working for Microsoft and Samsung, developing technological products that are currently used by billions of users in different ways. He has also been a tech entrepreneur for over 10 years with multiple successful exits and raising millions of GBP to fund the ventures. For his contributions to improving society through applications of embedded machine learning, he has been elected a Life Fellow of the Royal Society of Arts, named an MIT Innovator Under 35 in AI/Robotics in Europe, an Outstanding Achiever in Education, Science and Innovation at the India UK Achievers Honours and a World IP Review Leader since 2022. Over the years he has taught a wide range of modules in the field of Computer Science and Technology Entrepreneurship. Currently, he teaches Data Science modules including Programming, Object Oriented Programming, Artificial Intelligence, and Data Visualisation as part of the Data Science Degree apprenticeship course at York St John University.
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